artificial intelligence

the capacity of a computer to perform operations analogous to learning and decision making in humans, as by an expert system, a program for CAD or CAM, or a program for the perception and recognition of shapes in computer vision systems.

artificial intelligenceThe ability of a computer or other machine to perform actions thought to require intelligence. Among these actions are logical deduction and inference, creativity, the ability to make decisions based on past experience or insufficient or conflicting information, and the ability to understand spoken language.

Our Living Language: The goal of research on artificial intelligence is to understand the nature of thought and intelligent behavior and to design intelligent systems. A computer is not really intelligent; it just follows directions very quickly. At the same time, it is the speed and memory of modern computers that allows researchers to manage the huge quantities of data necessary to model human thought and behavior. An intelligent machine would be more flexible than a computer and would engage in the kind of "thinking" that people actually do. An example is vision. In theory, a network of sensors combined with systems for interpreting the data could produce the kind of pattern recognition that we take for granted as seeing and understanding what we see. In fact, developing software that can recognize subtle differences in objects (such as those we use to recognize human faces) is very difficult. The recognition of differences that we can perceive without deliberate effort would require massive amounts of data and elaborate guidelines to be recognized by an artificial intelligence system. According to the famous Turing Test, proposed in 1950 by British mathematician and logician Alan Turing, a machine would be considered intelligent if it could convince human observers that another human, rather than a machine, was answering their questions in conversation.

artificial intelligence (AI) The subfield of computer science concerned with the concepts and methods of symbolic inference by computer and symbolic knowledge representation for use in making inferences. AI can be seen as an attempt to model aspects of human thought on computers. It is also sometimes defined as trying to solve by computer any problem that a human can solve faster. The term was coined by Stanford Professor John McCarthy, a leading AI researcher. Examples of AI problems are computer vision (building a system that can understand images as well as a human) and natural language processing (building a system that can understand and speak a human language as well as a human). These may appear to be modular, but all attempts so far (1993) to solve them have foundered on the amount of context information and "intelligence" they seem to require. The term is often used as a selling point, e.g. to describe programming that drives the behaviour of computer characters in a game. This is often no more intelligent than "Kill any humans you see; keep walking; avoid solid objects; duck if a human with a gun can see you". See also AI-complete, neats vs. scruffies, neural network, genetic programming, fuzzy computing, artificial life. ACM SIGART (http://sigart.acm.org/). U Cal Davis (http://phobos.cs.ucdavis.edu:8001). CMU Artificial Intelligence Repository (http://cs.cmu.edu/Web/Groups/AI/html/repository.html). (2002-01-19)